Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Self-employed full time
Occupation: Prefer not to say
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Exercise;Use social media;Watch sports 
Devices used daily: Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Nearly every day
LLMs used: Character.AI;ChatGPT;Google Bard;Microsoft Bing AI 
LLM use cases: Brainstorming;Generic chatbot conversation;Analyze data;Generate art;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge;Translation;Solving math or logical problems 
Contexts of LLM use: Work;Learning;Personal;Creative or artistic 
Prompt 1: related words to indignant 
Prompt 2: shadow knight necromancer names
Prompt 3: damage comparison between 2d7+2 and 2d5+1 weapon
Prompt 4: what is non-citizen voting punishment
Prompt 5: grammar correction inquiry 
Prompt 6: days since march start
Prompt 7: leftist ideology critique 
Prompt 8: 2024 primary turnout rates
Prompt 9: poll results average calculation